{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 54
    },
    "colab_type": "code",
    "id": "QpGceqaETrLK",
    "outputId": "f1892acc-5942-45f8-bd0b-f2d2b2e25c59"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
     ]
    }
   ],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "dTZ4z2Tx92Sv"
   },
   "outputs": [],
   "source": [
    "!pip install fastai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "BgOsApcC96Q8"
   },
   "outputs": [],
   "source": [
    "import zipfile\n",
    "with zipfile.ZipFile(\"/content/drive/My Drive/Colab Notebooks/MachineHack/CatVsDog Computervision/Data.zip\",\"r\") as zip_ref:\n",
    "    zip_ref.extractall(\"input\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "16yuaIjV7gye",
    "outputId": "d04c9a49-5b62-411d-b76b-0dc8d72f15af"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Sample_Submission.csv', 'Train', 'Train.csv', 'Test', '.DS_Store']\n",
      "['Dogs', 'Cats', '.DS_Store', 'images']\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd \n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import cv2\n",
    "import glob\n",
    "print(os.listdir(\"input/Data\"))\n",
    "import shutil \n",
    "newpath = r'/content/input/Data/Train/images' \n",
    "if not os.path.exists(newpath):\n",
    "    os.makedirs(newpath)\n",
    "print(os.listdir(\"input/Data/Train\"))\n",
    "# Any results you write to the current directory are saved as output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4R6638mI7gzF"
   },
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "from fastai import *\n",
    "from fastai.vision import *\n",
    "import torch\n",
    "from fastai.callbacks.hooks import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "PpntUSxs7gzd"
   },
   "outputs": [],
   "source": [
    "data_folder = Path(\"input/Data/Train/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "PWfZttE27gzy"
   },
   "outputs": [],
   "source": [
    "data_path = \"input/Data/Train/images/\"\n",
    "path = os.path.join(data_path , \"*jpg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "QoJQMsV0oEGJ",
    "outputId": "c55a62f0-4a9d-4f0c-b547-9e127403ee32"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4747"
      ]
     },
     "execution_count": 44,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir = os.listdir(\"input/Data/Train/Cats\")\n",
    "len(dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "jL3NweOqLQqi"
   },
   "source": [
    "# Getting the data Ready in my convinient format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "NKp4SG5CiibT"
   },
   "outputs": [],
   "source": [
    "mypath = \"input/Data/Train/Dogs\"\n",
    "for root, dirs, files in os.walk(mypath):\n",
    "    for file in files:\n",
    "      src = mypath+\"/\"+file\n",
    "      dst = \"input/Data/Train/images\"\n",
    "      shutil.move(src, dst) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Z6MWeHw7kJiq"
   },
   "outputs": [],
   "source": [
    "mypath = \"input/Data/Train/Cats\"\n",
    "for root, dirs, files in os.walk(mypath):\n",
    "    for file in files:\n",
    "      src = mypath+\"/\"+file\n",
    "      dst = \"input/Data/Train/images\"\n",
    "      shutil.move(src, dst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4wjOIt2MrFOr"
   },
   "outputs": [],
   "source": [
    "mypath = \"input/Data/Test\"\n",
    "for root, dirs, files in os.walk(mypath):\n",
    "    for file in files:\n",
    "      src = mypath+\"/\"+file\n",
    "      dst = \"input/Data/Train/images\"\n",
    "      shutil.move(src, dst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Ll5grWZC7g0X"
   },
   "outputs": [],
   "source": [
    "train_df = pd.read_csv('input/Data/Train.csv')\n",
    "test_df = pd.read_csv('/content/input/Data/Sample_Submission.csv')[\"File_Name\"].to_frame()\n",
    "submit = pd.read_csv('/content/input/Data/Sample_Submission.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 419
    },
    "colab_type": "code",
    "id": "JohrNLjshlM0",
    "outputId": "f985a096-fdb8-4bec-d7a5-1e3bac89246d"
   },
   "outputs": [
    {
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      "text/plain": [
       "      File_Name  Category\n",
       "0     10846.jpg         1\n",
       "1      2360.jpg         1\n",
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       "...         ...       ...\n",
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       "\n",
       "[9471 rows x 2 columns]"
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     },
     "execution_count": 49,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 419
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    "colab_type": "code",
    "id": "Ya9u9FLIhncH",
    "outputId": "451e7c23-b992-4cc5-a6a2-8c33b8566af5"
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>File_Name</th>\n",
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       "      File_Name\n",
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       "2      8132.jpg\n",
       "3     16297.jpg\n",
       "4     20838.jpg\n",
       "...         ...\n",
       "4054  15376.jpg\n",
       "4055  19489.jpg\n",
       "4056   9762.jpg\n",
       "4057   1423.jpg\n",
       "4058  10488.jpg\n",
       "\n",
       "[4059 rows x 1 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "K5aePIdBLgH_"
   },
   "source": [
    "# Checking images with OpenCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "B5A59e67TJ-p"
   },
   "outputs": [],
   "source": [
    "train_imagesdf=[]\n",
    "for file1 in train_df[\"File_Name\"].values:\n",
    "      image = cv2.imread(\"/content/input/Data/Train/images/\"+file1)\n",
    "      train_imagesdf.append(image)\n",
    "test_imagesdf=[]\n",
    "for file1 in test_df[\"File_Name\"].values:\n",
    "      image = cv2.imread(\"/content/input/Data/Train/images/\"+file1)\n",
    "      test_imagesdf.append(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "MwOLeSvop17B",
    "outputId": "84c1234f-b8b9-4281-bd73-9079d0226c0c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13530"
      ]
     },
     "execution_count": 52,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir = os.listdir(\"input/Data/Train/images\")\n",
    "len(dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "eXFUloBQ7g0m",
    "outputId": "4a74bc05-9fa6-4b0a-d039-e4fb7b039ac5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((9471, 2), (4059, 1))"
      ]
     },
     "execution_count": 53,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.shape, test_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "B0v0qTWRRSwY"
   },
   "outputs": [],
   "source": [
    "# plt.imshow(train_imagesdf[10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "owwmITp4pNkR"
   },
   "outputs": [],
   "source": [
    "# plt.imshow(test_imagesdf[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 296
    },
    "colab_type": "code",
    "id": "6hCLzjVD7g2N",
    "outputId": "bd212d07-8c9b-45d9-f4e0-82a8ba2f2496"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe2a5669a20>"
      ]
     },
     "execution_count": 56,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='Category' , data=train_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "N1Hw5f6i7g22"
   },
   "outputs": [],
   "source": [
    "# train_images = train_imagesdf\n",
    "# test_images= test_imagesdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "GH7oyOU-LnwM"
   },
   "source": [
    "# Transformations!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "D81cIKh57g4E"
   },
   "outputs": [],
   "source": [
    "tfms = get_transforms(do_flip=True,flip_vert=False ,max_rotate=10.0, max_zoom=1.22, max_lighting=0.22, max_warp=0.0, p_affine=0.75,\n",
    "                      p_lighting=0.75)\n",
    "\n",
    "test_img = ImageList.from_df(test_df, path=data_folder, folder='images')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 440
    },
    "colab_type": "code",
    "id": "lcQwJL-hhMWo",
    "outputId": "0a14a5a0-142f-43cc-cd3f-1f99045d95bd"
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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\n",
      "image/png": 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\n",
      "text/plain": [
       "Image (3, 423, 313)"
      ]
     },
     "execution_count": 59,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_img[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "tHfoLqfX7g4S"
   },
   "outputs": [],
   "source": [
    "np.random.seed(145)\n",
    "## create source of train image databunch\n",
    "src = (ImageList.from_df(train_df, path=data_folder, folder='images')\n",
    "       .split_by_rand_pct(0.2)\n",
    "      #  .split_none()\n",
    "       .label_from_df()\n",
    "       .add_test(test_img))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "AV8c63-H7g4k"
   },
   "outputs": [],
   "source": [
    "data = (src.transform(tfms, size=299,padding_mode='reflection',resize_method=ResizeMethod.SQUISH)\n",
    "        .databunch(path='.', bs=32, device= torch.device('cuda:0')).normalize(imagenet_stats))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "PngMhBQu7g40",
    "outputId": "ffdcd969-bf8f-4f24-c47e-822942a9d14a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1]\n"
     ]
    }
   ],
   "source": [
    "print(data.classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "naFZfxFj7g5A"
   },
   "outputs": [],
   "source": [
    "#resnet152, densenet201, resnet101 ,resnet50\n",
    "# learn = cnn_learner(data=data, base_arch=models.resnet101, metrics=[FBeta(beta=1, average='macro'), accuracy],\n",
    "#                     callback_fns=ShowGraph)\n",
    "learn = cnn_learner(data=data, base_arch=models.resnet50, metrics=[FBeta(beta=1, average='macro'), accuracy],\n",
    "                    callback_fns=ShowGraph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "WjT7KSag7g5I"
   },
   "outputs": [],
   "source": [
    "learn.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 496
    },
    "colab_type": "code",
    "id": "UIZw_Lmx7g5S",
    "outputId": "082f841d-1b68-4dbd-ba7b-89f61758e83b"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "        <style>\n",
       "            /* Turns off some styling */\n",
       "            progress {\n",
       "                /* gets rid of default border in Firefox and Opera. */\n",
       "                border: none;\n",
       "                /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "                background-size: auto;\n",
       "            }\n",
       "            .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "                background: #F44336;\n",
       "            }\n",
       "        </style>\n",
       "      <progress value='0' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      0.00% [0/1 00:00<00:00]\n",
       "    </div>\n",
       "    \n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>f_beta</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table><p>\n",
       "\n",
       "    <div>\n",
       "        <style>\n",
       "            /* Turns off some styling */\n",
       "            progress {\n",
       "                /* gets rid of default border in Firefox and Opera. */\n",
       "                border: none;\n",
       "                /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "                background-size: auto;\n",
       "            }\n",
       "            .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "                background: #F44336;\n",
       "            }\n",
       "        </style>\n",
       "      <progress value='85' class='' max='236' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      36.02% [85/236 02:11<03:54 1.9805]\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LR Finder is complete, type {learner_name}.recorder.plot() to see the graph.\n",
      "Min numerical gradient: 1.32E-04\n",
      "Min loss divided by 10: 3.31E-03\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.lr_find()\n",
    "learn.recorder.plot(suggestion=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Jf9jSYquMFx7"
   },
   "source": [
    "# Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 713
    },
    "colab_type": "code",
    "id": "vHz9vVjN7g5f",
    "outputId": "d3ef8271-c6c1-4d55-cf2e-d52eec3dded2"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>f_beta</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.105845</td>\n",
       "      <td>0.026332</td>\n",
       "      <td>0.994715</td>\n",
       "      <td>0.994720</td>\n",
       "      <td>06:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.041690</td>\n",
       "      <td>0.006168</td>\n",
       "      <td>0.997886</td>\n",
       "      <td>0.997888</td>\n",
       "      <td>06:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.032022</td>\n",
       "      <td>0.010554</td>\n",
       "      <td>0.996301</td>\n",
       "      <td>0.996304</td>\n",
       "      <td>06:45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.019098</td>\n",
       "      <td>0.009159</td>\n",
       "      <td>0.996301</td>\n",
       "      <td>0.996304</td>\n",
       "      <td>06:45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n"
     ]
    }
   ],
   "source": [
    "lr = 3e-03\n",
    "learn.fit_one_cycle(4, slice(lr), wd=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SB4qTaZKMNUZ"
   },
   "source": [
    "with lower learning rate training again"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 416
    },
    "colab_type": "code",
    "id": "_jaznv8RHIvb",
    "outputId": "ea80d226-3ba7-4f4e-bfd3-2f23157176fd"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>f_beta</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.022154</td>\n",
       "      <td>0.007759</td>\n",
       "      <td>0.997886</td>\n",
       "      <td>0.997888</td>\n",
       "      <td>06:44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n",
      "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details. \n",
      "  warnings.warn(\"The default behavior for interpolate/upsample with float scale_factor will change \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learn.fit_one_cycle(1, slice(lr/2), wd=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "m414q5fPMTpC"
   },
   "source": [
    "Export"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "cxKDRB3CLXqg"
   },
   "outputs": [],
   "source": [
    "learn.export(file = Path(\"/content/drive/My Drive/Colab Notebooks/MachineHack/CatVsDog Computervision/export.pkl\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 17
    },
    "colab_type": "code",
    "id": "fpX_HUsOGQON",
    "outputId": "4f779a0c-db8c-4e59-af9e-ada509d8e945"
   },
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "preds,y,losses = learn.get_preds(with_loss=True)\n",
    "interp = ClassificationInterpretation(learn, preds, y, losses)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "bAmY2ijUMVqH"
   },
   "source": [
    "Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 311
    },
    "colab_type": "code",
    "id": "9TisSpKQGilE",
    "outputId": "9e5ddd12-0de5-463b-af4d-b6291b9a2ad4"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "interp.plot_confusion_matrix()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "SrWHjufMGsdI",
    "outputId": "c958f7ba-961d-48cc-a244-8a15370b705e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 1, 6), (1, 0, 1)]"
      ]
     },
     "execution_count": 103,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interp.most_confused()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "XXutPJ_2HyL_"
   },
   "outputs": [],
   "source": [
    "# pred_val,y = learn.TTA(ds_type=DatasetType.Valid)\n",
    "# from sklearn.metrics import f1_score, accuracy_score\n",
    "# valid_preds = [np.argmax(pred_val[i])+1 for i in range(len(pred_val))]\n",
    "# valid_preds = np.array(valid_preds)\n",
    "# y = np.array(y+1)\n",
    "# accuracy_score(valid_preds,y),f1_score(valid_preds,y, average='micro')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "l6JbynYZMCem"
   },
   "source": [
    "# Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 17
    },
    "colab_type": "code",
    "id": "2d3PCNiPH9Yp",
    "outputId": "06c8f990-5eb5-4f7a-a31d-368e249ef228"
   },
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "preds,_ = learn.TTA(ds_type=DatasetType.Test) # \n",
    "# preds,_ = learn.get_preds(ds_type = DatasetType.Test)\n",
    "labelled_preds = [np.argmax(preds[i]) for i in range(len(preds))]\n",
    "labelled_preds = np.array(labelled_preds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "CuOk9cPpM_4S"
   },
   "outputs": [],
   "source": [
    "preddf = pd.DataFrame(np.array(preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "P2EeIGzgIHwg"
   },
   "outputs": [],
   "source": [
    "df = pd.DataFrame({'File_Name':test_df['File_Name'], 'Category':labelled_preds})\n",
    "df[\"Category\"] = df[\"Category\"].astype(int)\n",
    "df[\"File_Name\"] = df[\"File_Name\"].astype(str)\n",
    "df.to_excel('submission5.xlsx', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 419
    },
    "colab_type": "code",
    "id": "YfHcqO3RIyjO",
    "outputId": "1fe4675e-c25b-4cc4-eb0a-b1535d1d5ca8"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>File_Name</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8121.jpg</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15486.jpg</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8132.jpg</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16297.jpg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20838.jpg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4054</th>\n",
       "      <td>15376.jpg</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4055</th>\n",
       "      <td>19489.jpg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4056</th>\n",
       "      <td>9762.jpg</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4057</th>\n",
       "      <td>1423.jpg</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4058</th>\n",
       "      <td>10488.jpg</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4059 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      File_Name  Category\n",
       "0      8121.jpg         0\n",
       "1     15486.jpg         0\n",
       "2      8132.jpg         0\n",
       "3     16297.jpg         1\n",
       "4     20838.jpg         1\n",
       "...         ...       ...\n",
       "4054  15376.jpg         0\n",
       "4055  19489.jpg         1\n",
       "4056   9762.jpg         0\n",
       "4057   1423.jpg         0\n",
       "4058  10488.jpg         0\n",
       "\n",
       "[4059 rows x 2 columns]"
      ]
     },
     "execution_count": 109,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "CatvsDog.ipynb",
   "provenance": []
  },
  "kernelspec": {
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